Along with recent remarkable progress in computers and networks, various kinds of information such as character data, image data, and audio data are stored and transmitted in computers or between networks. Of these data, an image and especially a multilevel image contains a very large quantity of information. In storing/transmitting the image, the enormous amount of data poses a problem.
Hence, for an application purpose such as an image database which allows image browsing through a network, images in the device for storing them are often compression-coded. To browse these images, all the compression-coded data must be transmitted and decoded. If the band of the network is insufficient, it takes a long time to display the image.
In such a case, only part of the compression-coded data is transmitted to display the image at a resolution lower than the original resolution. For, e.g., JPEG that is a compression-coding scheme recommended by the ISO and ITU-T, a hierarchical encoding scheme is defined whereby an image can be decoded at a resolution lower than the original resolution by a factor of a power of 2.
In JPEG, however, the encoding processing is complex, a reduced image or thumbnail image must be generated and encoded, and, for each layer of resolution necessary for decoding, the difference between a result obtained by decoding the reduced image and an image obtained by reducing the original image to that resolution must be encoded.
An encoding scheme that has recently received a great deal of attention is a scheme using discrete wavelet transformation. FIG. 17A is a block diagram showing the basic arrangement of a compression-coding/decoding apparatus based on discrete wavelet transformation. Referring to FIG. 17A, an image input section 1 outputs an image signal to be compression-coded, and transformation is performed by a discrete wavelet transform section 2 on the output side. The discrete wavelet transform section 2 executes 2-dimensional discrete wavelet transformation for the image signal and outputs transform coefficients. The transform coefficients are put together in units of predetermined frequency bands (to be referred to as subbands hereinafter), and quantized and converted into quantization indices by a quantization section 3 on the output side. The quantization indices are encoded by an entropy encoding section 4, so a code sequence is output.
FIG. 17D is a block diagram showing the arrangement of a decoding apparatus for decoding the thus generated code sequence. Referring to FIG. 17D, quantization indices decoded by an entropy decoding section 5 are reconstructed to transform coefficients by an inverse quantization section 6 on the output side. The reconstructed transform coefficients are inversely transformed by an inverse discrete wavelet transform section 7, so the image signal is reconstructed and output from an image output section 8.
FIG. 17B is a view showing the structure of subbands generated by the discrete wavelet transform section 2. Referring to FIG. 17B, a subband LL is the subband with the lowest frequency and can also be regarded as an image signal whose resolution is lowered by passing the original image through a low-pass filter and subsampling the image signal. Hence, when only the subband LL is decoded without decoding all subbands in decoding the image signal, and the decoded signal is normalized into the dynamic range of the original image signal, an image reduced to ¼ the original image in both the vertical and horizontal directions can be obtained.
When an image with a resolution higher by one level is necessary, subbands lower by one level, i.e., subbands HL2, LH2, and HH2 are decoded and inversely transformed together with the subband LL, as shown in FIG. 17C. An image whose resolution is lowered to ½ in both the vertical and horizontal directions is obtained, as shown in FIG. 17C.
As described above, in the encoding scheme using discrete wavelet transformation, a reduced image can be generated from a code sequence using the subband structure by transformation.
However, as described above, in the method using the subband structure of discrete wavelet transformation, the quality of the generated reduced image is not always sufficiently high. Especially, when the image contains information such as characters or graphic patterns, such patterns cannot be discriminated in some cases because an image without any high-frequency component is obtained by the above method.